About
I am a machine learning researcher with a background in mathematics and physics. I worked on natural language processing at Rasa, Amazon, and Lilt, with a particular focus on natural language processing.
To me, the rapid progress in deep learning theory, which is now catching up with modern practice, is the most interesting ongoing development in my field.
Curriculum Vitae
- 4 years of work experience as machine learning researcher
- PhD in mathematics from the University of Otago
- MSc in physics from the University of Potsdam in collaboration with the Max Planck Institute for Gravitational Physics
- Proficient in Python, the Wolfram Language / Mathematica, PyTorch, Tensorflow, and (to a lesser extent) C++
Date | Type | Description | Institution |
---|---|---|---|
2023 - present | Work | Research Scientist III | Lilt |
2023 | Study | Theoretical Physics for Deep Learning workshop | Aspen Center for Physics |
2022 - 2023 | Work | Research Scientist II, Alexa | Amazon |
2019 - 2022 | Work | Machine learning researcher | Rasa |
2021 | Award | Gavin Brown Best Paper Prize (contributor, shared) | Australian Mathematical Society |
2018 | Work | Software developer | FGEU mbH |
2018 | Teach | Teaching fellow | University of Otago |
2018 | Award | Exceptional Thesis Award | University of Otago |
2014 - 2018 | Study | PhD in mathematics | University of Otago |
2018 | Teach | Tutor for undergraduate physics | Univeristy of Otago’s Disability Information and Support Office |
2016 - 2017 | Work | Technology evangelist | Wolfram Research |
2015 - 2017 | Teach | Tutor for mathematics | University of Otago |
2011 - 2014 | Study | MSc in physics | University of Potsdam Max Planck Institute for Gravitational Physics |
2012 - 2014 | Work | Software developer | FGEU mbH |
2011 - 2013 | Teach | Tutor for undergraduate physics | University of Potsdam |
2012 | Study | Complex Quantum Systems (CoQuS) summer school | University of Vienna |
2011 | Study | DAAD, RISE in North America programme | York University |
Publications
The following list does not include blog posts, minor conference papers or presentations.
Machine Learning
Mosig, J. E. M., Mehri, S., & Kober, T. (2020). STAR: A Schema-Guided Dialog Dataset for Transfer Learning. ArXiv:2010.11853 [Cs].
Mosig, J. E. M., Vlasov, V., & Nichol, A. (2020). Where is the context? -- A critique of recent dialogue datasets. ArXiv:2004.10473 [Cs].
Vlasov, V., Mosig, J. E. M., & Nichol, A. (2019). Dialogue Transformers. ArXiv:1910.00486 [Cs].
Physics
Fräßdorf, C., & Mosig, J. E. M. (2017). Chemical-potential flow equations for graphene with Coulomb interactions. ArXiv Preprint ArXiv:1707.03920.
Fräßdorf, C., & Mosig, J. E. M. (2017). Keldysh functional renormalization group for electronic properties of graphene. Physical Review B, 95(12). https://doi.org/10.1103/PhysRevB.95.125412
Mosig, J. E. M. (2014). Spin Fields and Hidden Symmetries in Curved Spacetime [Master Thesis]. University of Potsdam.
Mosig, J. E. M. (2011). Electromagnetic Processes with Hadronic Final State Pion, Kaon, Antikaon [Bachelor Thesis]. Freie Universität Berlin.
Sea Ice & Ocean Modeling
Meylan, M. H., Bennetts, L. G., Mosig, J. E. M., Rogers, W. E., Doble, M. J., & Peter, M. A. (2018). Dispersion Relations, Power Laws, and Energy Loss for Waves in The Marginal Ice Zone. Journal of Geophysical Research: Oceans. https://doi.org/10.1002/2018JC013776
Mosig, J. E. M. (2018). Contemporary wave–ice interaction models [PhD, University of Otago].
Mosig, J. E. M., Montiel, F., & Squire, V. A. (2016). Water wave scattering from a mass loading ice floe of random length using generalised polynomial chaos. Wave Motion. https://doi.org/10.1016/j.wavemoti.2016.09.005
Mosig, J. E. M., Montiel, F., & Squire, V. A. (2015). Comparison of viscoelastic-type models for ocean wave attenuation in ice-covered seas. Journal of Geophysical Research: Oceans, 120(9), 6072–6090. https://doi.org/10.1002/2015JC010881
Mosig, J. E. M., Montiel, F., & Squire, V. A. (2015, September). Rheological models of flexural-gravity waves in an ice covered ocean on large scales. 7th International Conference on Hydroelasticity in Marine Technology. HYEL 2015, Split, Croatia.
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Last Update: 2023-03-09